Modelling and evaluating service quality measurement using neural networks

Effective measurement and analysis of service quality are an essential first step in its improvement. This paper discusses the development of neural network models for this purpose. A valid neural network model for service quality is initially developed. Customer data from a SERVQUAL survey at an auto-dealership network in The Netherlands provide the basis for model development. Different definitions of service quality measurement are modelled using the neural network approach. The perception-minus-expectation model of service quality was found not to be as accurate as the perception-only model in predicting service quality. While this is consistent with the literature, this study also shows that the more intuitively appealing but mathematically less convenient expectation-minus-perception model out-performs all the other service quality measurement models. The study also provides an analytical basis for the importance of expectation in the measurement of service quality. However, the study demonstrates the need for further study before neural network models may be effectively used for sensitivity analyses involving specific dimensions of service quality.